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import os | |
import gradio as gr | |
from langchain_ai21 import ChatAI21 | |
from ai21 import AI21Client | |
from ai21.models.chat import ChatMessage, DocumentSchema | |
# Set your AI21 API key | |
os.environ["AI21_API_KEY"] = "8T6NvXgGjhtlh9bh65jsNqb584BOorNM" | |
client = AI21Client(api_key="8T6NvXgGjhtlh9bh65jsNqb584BOorNM") | |
# Initialize the Jamba model | |
chatbot = ChatAI21(model="jamba-instruct", temperature=0.7) | |
# Define the function to handle chat | |
def chatbot_response(user_input): | |
# Wrap input into a dictionary with the expected format | |
messages = [ChatMessage(role='system', content='You are a concise factual based question answering assistant.'), | |
ChatMessage(role='user', content=user_input) | |
] | |
response = client.chat.completions.create(messages=messages, | |
model='jamba-1.5-large', | |
# max_tokens=4096, | |
# temperature=0.4, | |
# top_p=1.0, | |
# stop = [], ## ['####', '\n'], | |
# n=1, | |
# stream = False | |
) | |
return response.choices[0].message.content | |
# Create the Gradio interface | |
interface = gr.Interface( | |
fn=chatbot_response, | |
inputs="text", | |
outputs="text", | |
title="Jamba Chatbot", | |
description="A simple chatbot using AI21 Labs' Jamba technology." | |
) | |
# Launch the Gradio app | |
if __name__ == "__main__": | |
interface.launch() |